Triple
T22514737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rivoli Castle |
E556611
|
entity |
| Predicate | municipality |
P852
|
FINISHED |
| Object | Rivoli |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Rivoli | Statement: [Rivoli Castle, municipality, Rivoli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rivoli Context triple: [Rivoli Castle, municipality, Rivoli]
-
A.
Rivoli
chosen
Rivoli is a town in the Piedmont region of northern Italy, near Turin, known for its historic castle and strategic location.
-
B.
Piossasco
Piossasco is a municipality in the Metropolitan City of Turin in the Piedmont region of northwestern Italy.
-
C.
Bresso
Bresso is a municipality in the Metropolitan City of Milan in northern Italy, known for its dense urban setting and proximity to Milan.
-
D.
San Mauro Torinese
San Mauro Torinese is a municipality in the Metropolitan City of Turin in northern Italy, situated along the Po River just northeast of Turin.
-
E.
Marsella
Marsella is a small Colombian town known for its traditional architecture and coffee-growing culture in the Andean region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e2c3098819098a553133cc9515b |
completed | April 29, 2026, 1:26 a.m. |
Created at: April 16, 2026, 8:50 p.m.